We present GPS-seq, a theoretical framework that enables massively scalable, optics-free spatial transcriptomics. GPS-seq combines data from high-throughput sequencing with manifold learning to obtain the spatial transcriptomic landscape of a given tissue section without optical microscopy. In this framework, similar to technologies like Slide-seq and 10X Visium, tissue samples are stamped on a surface of randomly-distributed DNA-barcoded spots (or beads). The transcriptomic sequences of proximal cells are fused to DNA barcodes, enabling the recovery of a transcriptomic pixel image by high-throughput sequencing. The barcode spots serve as "anchors" which also capture spatially diffused "satellite" barcodes, and therefore allow computational reconstruction of spot positions without optical sequencing or depositing barcodes to pre-specified positions. In theory, it could generate 100 mm × 100 mm spatial transcriptomic images with 10-20 μm resolution by localizing 108 DNA-barcoded pixels with a single Illumina NovaSeq run. The general framework of GPS-seq is also compatible with standard single-cell (or single-nucleus) capture methods, and any modality of single-cell genomics, such as sci-ATAC-seq, could be transformed into spatial genomics in this strategy. We envision that GPS-seq will lead to breakthrough discoveries in diverse areas of biology by enabling organ-scale imaging of multiple genomic statuses at single-cell resolution for the first time.
Background: Aging and death are inevitable for most species and are of intense interest for human beings. Most mammals, including humans, show obvious aging phenotypes, for example, loss of tissue plasticity and sarcopenia. In this regard, fish provide attractive models because of their unique aging characteristics. First, the lifespan of fish is highly varied and some long-lived fish can live for over 200 years. Second, some fish show anti-aging features and indeterminate growth throughout their life.Because these characteristics are not found in mammalian model organisms, exploring mechanisms of senescence in fish is expected to provide new insights into vertebrate aging. Therefore, we conducted transcriptome analysis for brain, gill, heart, liver and muscle from 2-month-, 7-month-, 16month-and 39-month-old zebrafish. In addition, we downloaded RNA-seq data for sequential agerelated gene expression in brain, heart, liver and muscle of rat (1). These RNA-seq data from two species were compared, and common and species-specific features of senescence were analyzed.Results: Screening of differentially expressed genes (DEGs) in all zebrafish tissues examined revealed up-regulation of circadian genes and down-regulation of hmgb3a. Comparative analysis of DEG profiles associated with aging between zebrafish and rat showed both conserved and clearly different aging phenomena. Furthermore, up-regulation of circadian genes with aging and down-regulation of collagen genes were observed in both species. On the other hand, in zebrafish, up-regulation of autophagy related genes in muscle and atf3 in various tissues suggested fish-specific anti-aging characteristics. Consistent with our knowledge of mammalian aging, a tissue deterioration-related DEG profile was observed in rat. We also detected aging-associated down-regulation of muscle development and ATP metabolism-related genes in zebrafish gill. Correspondingly, hypoxia-related genes were systemically up-regulated in aged zebrafish, suggesting age-related hypoxia as a senescence modulator in fish. Conclusions:Our results indicate both common and different aging profiles between fish and mammals. Gene expression profiles specific to fish will provide new insight for future translational research.
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